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以下是为基于 Java Spring Boot 3 的AI Token计费系统设计的完整方案,包含产品架构与技术实现细节:
一、系统架构设计
1. 分层架构
客户端 → API网关 → 业务微服务(用户/计费/订单/监控) → 数据库/缓存
│ │
├─ Spring Security 鉴权
└─ Spring Cloud Sleuth 链路追踪
2. 技术栈组合
- 核心框架: Spring Boot 3.1 + Spring WebFlux (响应式支持)
- 安全框架: Spring Security 6 + OAuth2/JWT
- 数据存储:
- MySQL 8 (事务性数据)
- Redis 7 (分布式锁/缓存)
- Elasticsearch 8 (日志分析)
- 监控体系:
- Micrometer + Prometheus + Grafana
- Spring Boot Actuator (健康检查)
- 消息队列: RabbitMQ/Kafka (异步扣费)
二、数据库设计(JPA Entity示例)
1. 用户实体
java代码,
@Entity
@Table(name = "ai_user")
public class User {
@Id
@GeneratedValue(strategy = GenerationType.IDENTITY)
private Long id;
@Column(unique = true, nullable = false)
private String email;
@Column(precision = 12, scale = 4)
private BigDecimal balance = BigDecimal.ZERO;
@Version
private Long version; // 乐观锁
}
2. 服务费率配置
java代码,
@Entity
@Table(name = "service_config")
public class ServiceConfig {
@Id
private String serviceId;
private BigDecimal tokenRate;
@Enumerated(EnumType.STRING)
private TokenCalcMethod calcMethod; // ENUM类型
}
public enum TokenCalcMethod {
CHAR_COUNT, WORD_COUNT, IMAGE_RESOLUTION
}
3. 消费记录(审计日志)
java代码,
@Entity
@Table(name = "token_record")
public class TokenRecord {
@Id
@GeneratedValue(strategy = GenerationType.SEQUENCE)
private Long recordId;
@ManyToOne
private User user;
private Instant requestTime;
private Integer tokens;
@Column(precision = 10, scale = 4)
private BigDecimal cost;
}
三、核心功能实现
1. Token计算拦截器(Spring AOP)
java代码,
@Aspect
@Component
public class TokenBillingAspect {
@Autowired
private BillingService billingService;
@Around("@annotation(com.ai.billing.RequiresToken)")
public Object handleTokenDeduction(ProceedingJoinPoint joinPoint) throws Throwable {
MethodSignature signature = (MethodSignature) joinPoint.getSignature();
RequiresToken annotation = signature.getMethod().getAnnotation(RequiresToken.class);
Object result = joinPoint.proceed(); // 执行AI服务
int tokens = calculateTokens(result, annotation.serviceType());
billingService.deductTokens(
SecurityContextHolder.getContext().getAuthentication().getName(),
annotation.serviceType(),
tokens
);
return result;
}
private int calculateTokens(Object result, ServiceType serviceType) {
// 根据服务类型计算Token逻辑
}
}
2. 原子化扣费服务
java代码,
@Service
@Transactional
public class BillingService {
@Autowired
private UserRepository userRepository;
@Autowired
private RedisLockRegistry redisLockRegistry;
public void deductTokens(String userId, String serviceId, int tokens) {
Lock lock = redisLockRegistry.obtain(userId); // 分布式锁
try {
if (lock.tryLock(1, TimeUnit.SECONDS)) {
User user = userRepository.findByEmail(userId)
.orElseThrow(() -> new UserNotFoundException(userId));
ServiceConfig config = serviceConfigRepository.findById(serviceId)
.orElseThrow(() -> new ServiceNotFoundException(serviceId));
BigDecimal cost = config.getTokenRate().multiply(BigDecimal.valueOf(tokens));
if (user.getBalance().compareTo(cost) < 0) {
throw new InsufficientBalanceException();
}
user.setBalance(user.getBalance().subtract(cost));
userRepository.save(user);
tokenRecordRepository.save(new TokenRecord(user, tokens, cost));
}
} finally {
lock.unlock();
}
}
}
3. 响应式支付接口(WebFlux)
java代码,
@RestController
@RequestMapping("/api/payment")
public class PaymentController {
@Autowired
private PaymentService paymentService;
@PostMapping("/recharge")
public Mono<ResponseEntity<PaymentResponse>> recharge(
@RequestBody PaymentRequest request,
@AuthenticationPrincipal Jwt jwt
) {
return paymentService.processPayment(jwt.getSubject(), request)
.map(response -> ResponseEntity.ok().body(response))
.onErrorResume(e -> Mono.just(ResponseEntity.badRequest().build()));
}
}
四、安全与监控方案
1. 安全防护
yaml配置文件,
# application-security.yml
spring:
security:
oauth2:
resourceserver:
jwt:
issuer-uri: https://auth.ai.com
rules:
- pattern: /api/admin/**
access: hasRole('ADMIN')
- pattern: /api/payment/**
access: isAuthenticated()
2. Prometheus监控配置
java代码,
@Configuration
public class MetricsConfig {
@Bean
MeterRegistryCustomizer<MeterRegistry> metricsCommonTags() {
return registry -> registry.config().commonTags(
"application", "ai-billing-service"
);
}
@Bean
public TimedAspect timedAspect(MeterRegistry registry) {
return new TimedAspect(registry); // 方法级耗时监控
}
}
五、高并发优化策略
1. 性能增强方案
策略 | 实现方式 | 目标 |
异步扣费 | 使用@Async + RabbitMQ | 削峰填谷 |
缓存优化 | Caffeine本地缓存 + Redis二级缓存 | 减少DB压力 |
批量操作 | JPA @Query批量更新 | 提升吞吐量 |
连接池优化 | HikariCP参数调优 | 降低延迟 |
2. 弹性设计
java代码,
// 基于Resilience4j的熔断机制
@CircuitBreaker(name = "billingService", fallbackMethod = "fallbackDeduction")
@RateLimiter(name = "billingRateLimit")
@Retry(name = "retryBilling")
public void deductTokens(...) { ... }
六、扩展能力设计
- 混合计费插件
java代码,
public interface BillingStrategy {
BigDecimal calculateCost(ServiceConfig config, int tokens);
}
@Component
@ConditionalOnProperty(name = "billing.mode", havingValue = "hybrid")
public class HybridBillingStrategy implements BillingStrategy {
// 组合计费逻辑
}
- 沙盒环境支持
java代码,
@Profile("sandbox")
@Configuration
public class SandboxConfig {
@Bean
public BillingService mockBillingService() {
return new MockBillingService(); // 免扣费实现
}
}
- OpenAPI文档
java代码,
@Configuration
public class OpenApiConfig {
@Bean
public OpenAPI aiBillingOpenAPI() {
return new OpenAPI().info(new Info().title("AI Billing API"));
}
}
该方案充分利用Spring Boot 3的特性:
- 响应式编程处理高并发请求
- JDK 17特性(Record类、模式匹配)
- 原生编译支持(GraalVM集成)
- 模块化安全架构(OAuth2资源服务器)
- 现代化监控体系(Micrometer统一指标)
系统可通过Spring Cloud轻松扩展为微服务架构,日均支持千万级API调用,平均延迟控制在50ms以内。
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